Effect of mentalization-based family therapy on depressive symptoms and non-suicidal self-injury behavior in adolescents with major depressive disorder
Bibliographic record
Abstract
BackgroundThe major depressive disorder has high prevalence among adolescents， and non-suicidal self-injury （NSSI） behaviors frequently occur among patients， therefore， major depressive disorder in adolescents has become the researching focus.ObjectiveTo explore the effect of mentalization-based family therapy （MBFT） on depressive symptoms and NSSI behavior in adolescents with major depressive disorder， and to provide references for the rehabilitation of major depressive disorder in adolescents.MethodsA total of 90 adolescent patients with major depression disorder who met the diagnostic criteria of International Classification of Diseases， 10th edition （ICD-10） for depressive disorders and attended Wuhan Mental Health Center from January to December 2022 were selected， and were assigned into study group （n=44） and control group （n=46） using random number table method. All participants received routine intervention， based on this， study group added a 60-minute MBFT intervention once a week for 8 weeks. Before the intervention and at the end of 1st， 2nd，4th and 8th week，the two groups were assessed using Hamilton Depression Scale-24 item （HAMD-24）， General Self-Efficacy Scale （GSES）， Pittsburgh Sleep Quality Index （PSQI） and Ottawa Self-injury Inventory （OSI）.ResultsThe repeated measures analysis of variance reported a statistical main effect of time， main effect of group， and interaction effect between time and group at the baseline and the end of 1st， 2nd， 4th and 8th week of treatment in HAMD-24 score （F=69.621， 15.428， 29.623， P˂0.05）， OSI score （F=176.642， 37.682， 21.873， P˂0.05）， GSES score （F=215.236， 57.421， 27.857， P˂0.05） and PSQI score （F=268.541， 61.863， 33.867， P˂0.05）. Individual effect analysis discovered a statistical difference between study group and control group at the end of 2nd， 4th and 8th week of treatment in HAMD-24 score （t=5.567， 8.645， 6.233， P˂0.01）， OSI score （t=3.675， 11.817， 9.632， P˂0.01）， GSES score （t=23.462， 31.709， 12.750， P˂0.01） and PSQI score （t=9.664， 22.457， 9.333， P˂0.01）.ConclusionMBFT may improve depressive symptoms， NSSI behavior， sleep quality and self-efficacy in adolescents with major depressive disorder. ［Funded by 2022 Natural Science Foundation Project of Hubei Province （number， 2022CFB483）］
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".